CN108836374B

CN108836374B - Image reconstruction method and device

Info

Publication number: CN108836374B
Application number: CN201810332952.1A
Authority: CN
Inventors: 宁鹏; 杨龙; 高鹏; 赵玉秋; 贺亮
Original assignee: Neusoft Medical Systems Co Ltd
Current assignee: Shenyang Zhihe Medical Technology Co ltd
Priority date: 2018-04-13
Filing date: 2018-04-13
Publication date: 2021-11-30
Anticipated expiration: 2038-04-13
Also published as: CN108836374A

Abstract

The present disclosure provides an image reconstruction method and apparatus, wherein the method includes: acquiring single events of adjacent first time slices and second time slices; respectively carrying out time sequencing on each single event collected in the first time slice and the second time slice; splicing the target time period of the first time slice with the second time slice to obtain a new time slice; filtering the new time slice by single event; performing coincidence judgment on the single event in the new time slice after the single event is filtered to obtain a coincidence event; and reconstructing an image according to the coincidence event.

Description

Image reconstruction method and device

Technical Field

The present disclosure relates to medical imaging technologies, and in particular, to an image reconstruction method and apparatus.

Background

In the diagnostic imaging technique in the medical field, for example, a Positron Emission Tomography (PET) system, a tracer is generally injected into a body of a scanned object, and a PET detector detects gamma photon pairs released by Positron annihilation events occurring in the body, so as to analyze the presence of Positron e +, obtain the concentration distribution of the tracer in the detected scanned object, and determine the focus of a disease. When a detector detects two gamma photons from the same positron annihilation event, it may be said that a pair of coincident events is detected. One of the bases in determining coincidence events is time coincidence, i.e., the single-event time of a single event corresponding to the detection of two gamma photons by the detector is generally in the time interval range of several nanoseconds to several tens of nanoseconds, which is called a coincidence time window. Two single events for two gamma photons are not coincident events if their single event times are separated by more than the coincidence time window.

The time coincidence determination is generally to sort all the single event times collected in one time slice according to a sequence, and then sequentially compare whether two adjacent single event times are in a coincidence time window. The so-called time slices are actually time slices divided into successive time slices on the time axis, each time slice being a time slice, and each Block module of the PET detector acquires a single event time of gamma photons only once within a time slice. However, the current time coincidence determination method may still cause the loss of the true coincidence event count rate, thereby affecting the quality of image reconstruction.

Disclosure of Invention

In view of the above, the present disclosure provides an image reconstruction method and apparatus to improve image reconstruction quality.

Specifically, the present disclosure is realized by the following technical solutions:

in a first aspect, an image reconstruction method is provided, the method including:

acquiring single events of a first time slice and a second time slice;

respectively carrying out time sequencing on each single event collected in a first time slice and a second time slice, wherein the first time slice and the second time slice are two adjacent time slices;

splicing the target time period of the first time slice with the second time slice to obtain a new time slice; the target time period includes: a first time window and a second time window located at the end of the first time slice, wherein the first time window is adjacent to the second time slice;

performing single event filtering on the new time slice, including: removing the target single event in the first time slice, wherein the target single event is a single event of which the timestamp is positioned in a second time window in the time-sequenced coincidence events, and removing the single event in the first time window in the second time slice;

performing coincidence judgment on the single event in the new time slice after the single event is filtered to obtain a coincidence event;

and reconstructing an image according to the coincidence event.

In a second aspect, there is provided an image reconstruction apparatus, the apparatus comprising:

the data acquisition module is used for acquiring single events of the first time slice and the second time slice;

the sequencing processing module is used for respectively carrying out time sequencing on each single event collected in a first time slice and a second time slice, wherein the first time slice and the second time slice are two adjacent time slices;

the time splicing module is used for splicing the target time slice of the first time slice with the second time slice to obtain a new time slice; the target time period includes: a first time window and a second time window located at the end of the first time slice, wherein the first time window is adjacent to the second time slice;

the event filtering module is used for filtering the single event of the new time slice, and comprises: removing the target single event in the first time slice, wherein the target single event is a single event of which the timestamp is positioned in a second time window in the time-sequenced coincidence events, and removing the single event in the first time window in the second time slice;

the coincidence processing module is used for carrying out coincidence judgment on the single event in the new time slice after the single event is filtered to obtain a coincidence event;

and the image reconstruction module is used for reconstructing an image according to the coincidence event.

According to the image reconstruction method and device provided by the disclosure, the target time period of the first time slice is spliced with the second time slice, so that the counting rate of the true coincidence event can be improved, the loss of the true coincidence event in time coincidence judgment is reduced, and the quality of image reconstruction is improved.

Drawings

Fig. 1 is a system configuration of a PET apparatus shown in an exemplary embodiment of the present disclosure;

FIG. 2 is a multi-channel processing architecture conforming to a processing plate shown in an exemplary embodiment of the present disclosure;

FIG. 3 is a diagram illustrating an adjacent time slice coincidence determination, according to an exemplary embodiment of the present disclosure;

FIG. 4 is a flowchart illustrating an image reconstruction method according to an exemplary embodiment of the present disclosure;

FIG. 5 is a diagram illustrating an adjacent time slice coincidence determination, according to an exemplary embodiment of the present disclosure;

FIG. 6 is a diagram illustrating an adjacent time slice coincidence determination, according to an exemplary embodiment of the present disclosure;

fig. 7 is a schematic structural diagram of an image reconstruction apparatus according to an exemplary embodiment of the present disclosure.

Detailed Description

Reference will now be made in detail to the exemplary embodiments, examples of which are illustrated in the accompanying drawings. When the following description refers to the accompanying drawings, like numbers in different drawings represent the same or similar elements unless otherwise indicated. The implementations described in the exemplary embodiments below are not intended to represent all implementations consistent with the present disclosure. Rather, they are merely examples of apparatus and methods consistent with certain aspects of the present disclosure, as detailed in the appended claims.

Fig. 1 illustrates a system configuration of a PET apparatus, and the PET apparatus 11 may include: a detection device 12, a plurality of time scaling boards 13 and a coincidence processing board 14. Where the detection apparatus 12 may include a plurality of BLOCK modules 15, each BLOCK module 15 including a plurality of crystals, a positron annihilation event 16 occurring within a scanned object located within the interior space of the detection apparatus 12 will produce two gamma photons that may be received by the crystals in the BLOCK modules 15.

As shown in fig. 1, the PET detector 12 includes a plurality of BLOCK modules 15, and each BLOCK module 15 can collect at most one gamma photon in a time slice. If the time at which the crystal receives a gamma photon is referred to as the single event time, then the single event time of the photon will be calibrated by the time calibration board 13 to which the BLOCK module is connected after the BLOCK module receives the gamma photon. For example, assuming that a crystal in a BLOCK module 15 detects a gamma photon generated in an annihilation event, the BLOCK module will generate an electrical trigger signal, which will be transmitted to a time scaling board 13, where the time scaling board 13 may be a hardware circuit with a similar structure such as an FPGA (Field-Programmable Gate Array), and the single-event time of the gamma photon detection can be determined by the time scaling board 13.

As shown in fig. 1, each BLOCK module 15 is connected to one time scaling board 13, but one time scaling board 13 may be connected to a plurality of BLOCK modules 15, and assuming that the PET apparatus has m time scaling boards 13 in total, and each time scaling board 13 is connected to n BLOCK modules 15, where m and n are natural numbers greater than 1, there are "m × n" BLOCK modules 15 in total. If each BLOCK module 15 detects at most one gamma photon within a time slice, then there are at most "m x n" single event timestamps for a time slice.

The single event times calibrated by the respective time calibration boards 13 may be transmitted to the coincidence processing board 14, and the coincidence processing board 14 stores or buffers the single event times, and performs time coincidence determination based on the single event times. For example, the coincidence processing board 14 can determine which two single-event times are within the coincidence time window, and if within the coincidence time window, the two gamma photons corresponding to the two single-event times may be generated by the same annihilation event and be the coincidence event. When the time coincidence judgment is carried out, the single event times in one time slice can be sequenced according to the occurrence time, and the judgment of the coincidence time window is carried out after the sequencing.

As mentioned above, each time scaling board 13 may continuously transmit the collected single event times to the coincidence processing board 14, for example, the collected single event times in the first time slice, the collected single event times in the second time slice, the collected single event times in the third time slice, etc., and the single event times in each time slice are at most "m × n". The coincidence event determination method provided by the embodiment of the application may be executed by the coincidence processing board 14, and the coincidence processing board 14 may perform coincidence determination on the single event time of each received time slice by using the method, where the coincidence determination refers to time coincidence determination, and the following coincidence event is also an event satisfying time coincidence.

Referring to fig. 2, in this example, the coincidence processing board 14 can process the single event times of the time slices in parallel by using multiple channels, and each channel processes the single event time in one time slice. For example, if a time length of one time slice is 200ns and a time length for ordering and determining the single event times collected in one time slice is 700ns, if only one channel is used for processing, when the channel has not processed the single event time of the current time slice, the single event time of the next time slice will come and may cover the time of the current time slice. Therefore, the present example can design multi-channel parallel processing, and satisfy the following conditions: the first time length is greater than or equal to a second time length, the first time length is the total time length of a plurality of time slices corresponding to the multiple channels, and the second time length is the time length of processing one time slice by each channel.

Taking the four channels shown in fig. 2 as an example, it is still assumed that the time length of one time slice is 200ns, and the time length for ordering and coincidence determination of the single event times collected in one time slice is 700 ns. In FIG. 2, single event times for a first time slice are processed in the first channel T1, times for a second time slice are processed in the second channel T2, times for a third time slice are processed in the third channel T3, and times for a fourth time slice are processed in the fourth channel T4. When the time of the fifth time slice arrives, the time of the first four time slices, that is, 4 × 200ns is 800ns, at this time, the first channel T1 has already processed the time of the first time slice (the time length for processing one time slice is 700ns <800ns), and is idle, and the single event time collected in the fifth time slice may be sent to T1 for processing. Similarly, the single event time for the sixth time slice may be sent to T2 for processing, and so on. This way the continuity of the time slice processing is guaranteed without causing the covering and loss of the time stamps. The method for ordering and processing the coincidence determination of the single event times of a time slice in each of the four channels shown in fig. 2 may be the same.

In the general time coincidence determination, coincidence determination may be performed between all single event times collected in the same time slice, for example, coincidence determination is performed between single event times of a first time slice, coincidence determination is performed between single event times of a second time slice, and generally no inter-time slice coincidence determination is performed between a single event time of the first time slice and a single event time of the second time slice. However, this approach may cause the loss of coincidence events formed between two adjacent time slices, reducing the true coincidence count rate. Thus, the applicant has proposed compliance across time slices in the application (application number: 201710822519.1 filing date: 2017-09-13), to which reference may be made in detail.

However, the applicant has found that improvements can be made to the above-mentioned application of the coincidence scheme across time slices to further increase the true coincidence count rate. For example, taking fig. 3 as an example, taking two adjacent time slices, "the first time slice" and "the second time slice" as an example, for example, the last time window of the first time slice may be spliced with the second time slice, assuming that the time length of one time slice is 200ns, and the time resolution capability of the system is 50ps, then 200ns/50ps equals 4000 time units in one time slice, and if the time length of one time window is 5ns, then one time window corresponds to 5ns/50ps equals 100 time units. According to the aforementioned application (hereinafter referred to as a prior application) (application No. 201710822519.1 application date: 2017-09-13), after the coincidence determination is performed by splicing the single event of the last time window of the first time slice with the second time slice, the coincidence event in the last time window of the second time slice can be removed again to prevent the repetition of the determination.

However, applicants have discovered that it is also possible for a single event in the last time window of the first time slice, as exemplified in FIG. 3, to form a coincident event with a single event in the second last time window, such as coincident event 31 in FIG. 3. If the scheme of the prior application is followed, then coincident events like the coincident event 31 may be lost, reducing the true coincident count rate. Furthermore, as illustrated in fig. 3, it is also possible for a single event 32 in a coincident event 31 to form a coincident event 33 with a single event in the second last time window, and the coincident event 33 will be output as a coincident event in the first time slice, which will result in the single event 32 actually participating in the repeated determination, both in the formation of the coincident event 31 and in the formation of the coincident event 33.

The present application provides an image reconstruction method, which may be performed by a PET device and which may further improve the true coincidence count rate, avoid repeated determination, and thus improve the quality of image reconstruction, see the example of fig. 4. The method is to determine time coincidence of the time of a single event, and although single event filtering or single event splicing is mentioned in the following description of the method, it can be understood by those skilled in the art that the method may be to perform filtering or splicing on a timestamp of a single event. As shown in fig. 4, the following processes may be included:

in step 400, a single event for a first time slice and a second time slice is collected.

In this step, two adjacent time slices may be referred to as a first time slice and a second time slice, respectively. The first time slice and the second time slice are not limited in the sequence position relationship on the time axis, for example, the first time slice may be located before the second time slice on the time axis, or may be located after the second time slice. However, in the following example, the first time slice is described before the second time slice.

In step 402, the single events collected in a first time slice and a second time slice are respectively time-sequenced, wherein the first time slice and the second time slice are two adjacent time slices.

For example, the single events collected within the first and second timeslices may be time ordered separately. Each single event may have a timestamp indicating the time of receipt of the single event, for example, the timestamp may be the identification of the aforementioned time unit, the timestamp of one single event is 1000 indicating that the single event was detected at the 1000 th time unit (corresponding to the 1000 x 50ps time position within one time slice counted from the start time), and the timestamp of another single event is 1500 indicating that the single event was detected at the 1500 th time unit.

In step 404, the target time period of the first time slice is spliced with the second time slice to obtain a new time slice.

For example, the target time period may include: the time window comprises a first time window and a second time window which are positioned at the end parts of a first time slice, and the first time window is adjacent to the second time slice. Such as the example of fig. 3, time window C1 may be referred to as a first time window and time window C2 may be referred to as a second time window.

One way may be "from front to back splicing", that is, when the first time slice is located before the second time slice on the time axis, such as the time slice splicing way illustrated in fig. 3, the target time period is the last two time windows of the first time slice.

Another way may be "back-to-front stitching", i.e. when the first time slice is located after the second time slice on the time axis, the target time period may be the first two time windows of the first time slice. For example, it is assumed that the time ordering of the first time slice and the second time slice in fig. 3 on the time axis can be reversed, and the two first time windows of the first time slice located at the back are spliced with the second time slice.

In the example of the present application, the "front-to-back splicing" illustrated in fig. 3 will be described as an example, but it is understood that the "front-to-back splicing" may still adopt the coincidence determination method.

For example, in the example of fig. 3, the whole of the last two time windows of the first time slice and the second time slice after splicing can be referred to as a new time slice, see the schematic of fig. 3.

The splicing of the two time slices how this step is performed will be described separately later.

In step 406, single event filtering is performed on the new time slice.

Before the single event filtering of the step is carried out, the first time slice executes the coincidence judgment, the coincidence event in the first time slice is obtained, and the obtained coincidence event has application in the step.

The single event filtering of this step may include two aspects of filtering:

in one aspect, a target single event in a first time slice may be removed, the target single event being a single event with a timestamp within a second time window in time-ordered coincident events. For example, taking fig. 3 as an example, after performing coincidence determination in the first time slice, a plurality of coincidence events are obtained, and the coincidence events may be double coincidence or triple coincidence. In the double coincidence or the triple coincidence, if the timestamp of at least one single event is located within the second time window (time window C2), the at least one single event is removed. A single event (which does not coincide with a single event within the penultimate or penultimate time window) may not be removed if its timestamp lies within the second time window.

On the other hand, single events in the first time window in the second time slice can be removed. For example, taking fig. 3 as an example, the first time window within the second time slice may be time window C3, because this time window C3 will be stitched to the next time slice (e.g., the third time slice) of the second time slice, and the coincident event within this time window C3 will also be output as, for example, a coincident event of the third time slice.

It should be noted that, in the filtering in the above two aspects, in the first time slice, the target single event in the coincidence event that has been determined to have been met is removed, and if the target single event is a separate single event (i.e. not forming a coincidence with other single events), the filtering may not be performed; in the second time slice, all single events in the first time window are directly filtered, and coincidence judgment is not performed in advance, namely, the single events are filtered as long as the single events are in the first time window, and the filtered single events are spliced to the next time slice to perform coincidence judgment.

For example, two single events in the coincident events 33 in fig. 3 are both in the time window C2, the two single events may be removed, and the single event in the time window C3 is removed, and the single event in the time window C3 is spliced to the next time slice for coincidence determination.

For another example, as in the example of FIG. 5, where the coincident event 34 is a triple coincidence, where a single event 35 is located within the time window C2, the single event 35 may be removed.

As another example, in coincident events 36 illustrated in FIG. 6, both single event 37 and single event 38 are located within time window C2, and both single events may be filtered out.

By filtering out single events in the time window C2, it is possible to avoid these single events from again matching the time window within the time window C1, and by filtering out single events in the time window C3, these measures avoid repeated matching decisions; moreover, the independent single event in the time window C2 can continue to form coincident events with the single event in the time window C1, thereby increasing the true coincident count rate.

In step 408, a coincidence determination is performed on the single event in the new time slice after the single event filtering to obtain a coincidence event.

After filtering in step 406, the remaining single events will be jointly subjected to a coincidence determination. As in the example of fig. 3, the "coincidence decision segment" indicates a time period in which a single event actually making a coincidence decision is located, wherein the single event in the time window C3 has been filtered out, and a part of the single event in the time window C2 has also been filtered out. After the coincidence judgment is carried out on the remaining single events in the coincidence judgment section, the coincidence events can be directly output.

In this example, determination of double coincidence and determination of triple coincidence may be included. More than three coincidences can be discarded altogether.

Wherein the determination of double coincidence can be made in the usual manner, and triple coincidence is similar to double coincidence, adding to the determination of FOV and energy summation.

For example, determination of triple coincidence may be performed as follows:

if three events exist in a time window at the same time, the three events form triple coincidence, and only two events in the three events are true coincidence events, so that the three events need to be further judged. The FOV decision is first. The FOV judgment is to verify whether the positions of crystals forming the coincidence events meet the space coincidence judgment condition or not, three coincidence lines formed by the three events are all in the effective range of the FOV, and if the three events are met at the same time, the energy judgment is carried out; if not, directly filtering out the unsatisfied coincidence line. The second is energy judgment. And the energy judgment is to respectively add the energy information of the three events two by two, select the crystal energy and the largest one of the coincidence lines as an effective coincidence line, and form a true coincidence event by two single events corresponding to the effective coincidence line for output.

In step 410, image reconstruction is performed based on the coincidence events.

According to the image reconstruction method, the target time period of the first time slice is spliced with the second time slice, so that the counting rate of the true coincidence events can be improved, the loss of the true coincidence events in time coincidence judgment is reduced, and the quality of image reconstruction is improved.

The process of splicing the target time segment of the first time segment with the second time segment in step 404 is described as follows, and the process can be controlled by a state machine, and the splicing of the two time segments is realized through the jumping among a plurality of states of the state machine.

Before splicing, after time sequencing is performed on the single events collected in the first time slice and the second time slice, the timestamps of the single events in the time slices to be spliced together can be modified. For example, the minimum timestamp of the timestamp interval corresponding to the target time period may be subtracted from the timestamp of each single event in the target time period. And adding a timestamp interval difference value to the timestamp of each single event in the second time slice, wherein the timestamp interval difference value is the maximum timestamp minus the minimum timestamp in the timestamp interval.

For example, one time slice corresponds to 4000 time units, and one time window corresponds to 100 time units, so if the target time period is the last two time windows of the time slice, the time stamp interval corresponding to the target time period is a time stamp interval of 3800 to 4000. I.e., single events with timestamps between 3800-4000 will be stitched into the next time slice.

Assuming that the last two time windows of the first time slice correspond to the interval of 3800-4000 and the time unit range of the second time slice is 0-4000, if { 3800-4000, 0-4000 } is directly spliced, the sorted result may be affected. Therefore, in this example, 3800 is subtracted from each timestamp corresponding to each single event in the last two time windows (i.e., the target time period) of the first time slice, where the 3800 is the minimum timestamp in the timestamp intervals 3800 to 4000 corresponding to the target time period. And adding 200 to the timestamp of each single event in the second time slice, wherein 200 is the maximum timestamp 4000 minus the minimum timestamp 3800 in the timestamp intervals 3800-4000 corresponding to the target time slice. And then splicing the timestamps of the two time slices after the timestamps are modified. After the time stamps are modified, the time stamp range of the target time period of the first time slice is 0-200, the time stamp range of the second time slice is 200-4200, the corresponding interval of the new time slice is { 0-200, 200-4200 }, and the length of the spliced time slice is 4200.

The state machines may include a first state machine and a second state machine.

The first state machine is used for respectively writing the time stamp of each single event in the target time period of the first time slice and the time stamp of each single event of the second time slice into a preset memory by controlling jumping among a plurality of states so as to splice the time stamp in the target time period and the time stamp of the second time slice in the memory.

And the second state machine is used for sending the time stamp in the memory to the coincidence judgment module for coincidence judgment when the effective time stamp exists in the target time period of the first time slice or the second time slice by controlling the jumping among the plurality of states.

As exemplified below:

the time stamps of the single events to be sent into the splicing in the first time slice can be written into the buffer 2, the time stamps sequenced in the second time slice are written into the buffer 1, and then the time stamps in the buffer 1 are written into the buffer 2, so that the splicing of the two time slices is completed in the buffer 2.

The first state machine may be a state machine 1, which is used to complete the splicing function of the time slices and may include three states; the second state machine may be the state machine 2, and is used to control whether to send the timestamp in the buffer 2 to the coincidence judging module for processing, and may include five states. In addition, in the following description, the first time slice may be referred to as a previous time slice, and the second time slice may be referred to as a current time slice. The working mechanism in the state machine is that the state machine is in a starting state, and different states are jumped according to different conditions currently met in the starting state.

A state machine 1: there are 3 states in total.

State 1:

since there is no timestamp of the previous time slice after power-on reset, when the buffer 1 is not empty, all timestamps in the buffer 1 are read out and written into the buffer 2. And after all the timestamps on the current time slice are written, keeping the timestamps in the buffer 2 for standby, and simultaneously outputting an identification signal for finishing the time slice splicing function so as to jump to the state 2 according to the identification signal.

State 2:

and writing the timestamp of the previous time slice sent into the current time slice into the buffer 2, wherein the timestamp of the previous time slice sent into the current time slice refers to the timestamp in the target time period in the previous time slice and is the timestamp to be spliced with the current time slice. And after all the writing is finished, jumping to the state 3. If the previous time slice has no valid timestamp, then state 3 is directly jumped. Wherein, the valid timestamp is that the single event identified by the detector meets the energy requirement. When a photon is identified by the detector (the detector detects a photon, i.e. acquires a single event), it contains two pieces of information, one time stamp, i.e. timestamp, and the other energy information. Whether the photon is valid or not can be judged according to the energy information of the identified photon, namely when the photon meets the energy requirement, the corresponding timestamp can be considered as a valid timestamp.

State 3:

if the buffer 1 is not empty, all the time stamps in the buffer 1 are read out and written into the buffer 2. All timestamps on the current time slice are completely written and then are left in a buffer 2 for standby, and meanwhile, an identification signal for completing the time slice splicing function is output, and the state 2 is skipped; and if the current time slice has no effective timestamp, directly skipping to the state 2 after outputting an identification signal for finishing the time slice splicing function.

It should be noted here that the time slices are collected continuously, i.e. continuously, and therefore the state machine 1 continuously performs the process of jumping between the states 2 and 3. State 1 is a special case, because the device is powered on from the beginning, that is, there is no timestamp before the first time slice, and only the timestamp of the current time slice needs to be written into the buffer 2 directly, which is consistent with state 3. Through multiple jumps between the state 2 and the state 3, the timestamp in the target time period of the previous time slice and the timestamp of the current time slice can be completely written into the buffer 2, and the splicing is completed in the buffer 2.

And (3) state machine 2: there are 5 states in total. It should be noted that, the jumping among the five states also requires attention to the continuous acquisition of the time slices, so that the state machine 2 determines whether to send the time slices to the coincidence determination module after completing one splicing, and then determines whether to send the time slices to the coincidence determination module for the next splicing.

State 1:

the first splicing after resetting is not needed to consider whether the valid timestamp exists in the previous time slice at the moment, because the data of the previous time slice does not exist at the starting moment. If the current time slice has the timestamp, after the identification signal of the time slice splicing function is output, the timestamp is sent to a coincidence judgment module for continuing coincidence processing; if not, the coincidence judgment is ended, and simultaneously the state 2 is jumped.

State 2:

if the current time slice is sequenced at first and has an effective timestamp, sending the timestamp to a coincidence judgment module for processing after the identification signal of the time slice splicing function is output, and keeping the state 2 unchanged;

if the current time slice is sequenced first and is finished and the current time slice has no effective timestamp, skipping to a state 3;

if the previous time slice finishes sequencing and has a valid timestamp, jumping to a state 4;

if the previous time slice finishes sequencing first and does not have a valid timestamp, jumping to a state 5;

state 3:

waiting for the end of the sequencing of the previous time slice, if the previous time slice has a valid timestamp, after the identification signal of the time slice splicing function is output, sending the timestamp into a coincidence judgment module for processing, and jumping to a state 2; if the previous time slice has no valid timestamp, the judgment is finished, and the state 2 is directly jumped;

and 4:

after the identification signal of the time slice splicing function is output, the timestamp is sent to a coincidence judgment module for processing, and a state 2 is skipped;

and state 5:

waiting for the end of sequencing of the current time slice, if the current time slice has a valid timestamp, sending the timestamp into a coincidence judgment module for processing after the identification signal of the time slice splicing function is output, and jumping to a state 2; if the current time slice has no valid timestamp, the coincidence judgment is finished, and the state 2 is directly jumped.

The present disclosure also provides an image reconstruction apparatus that may be logically divided into a plurality of modules. Referring to fig. 7, the device may be, for example, a PET device, which may include: a data acquisition module 71, a sorting processing module 72, a time stitching module 73, an event filtering module 74, a coincidence processing module 75, and an image reconstruction module 76. Wherein the content of the first and second substances,

a data collecting module 71, configured to collect single events of a first time slice and a second time slice;

the sequencing processing module 72 is configured to perform time sequencing on each single event collected in a first time slice and a second time slice respectively, where the first time slice and the second time slice are two adjacent time slices;

a time splicing module 73, configured to splice the target time period of the first time slice with the second time slice to obtain a new time slice; the target time period includes: a first time window and a second time window located at the end of the first time slice, wherein the first time window is adjacent to the second time slice;

an event filtering module 74, configured to perform single event filtering on the new time slice, including: removing the target single event in the first time slice, wherein the target single event is a single event of which the timestamp is positioned in a second time window in the time-sequenced coincidence events, and removing the single event in the first time window in the second time slice;

a coincidence processing module 75, configured to perform coincidence determination on the single event in the new time slice after the single event is filtered, so as to obtain a coincidence event;

and an image reconstruction module 76 for performing image reconstruction according to the coincidence event.

In one example, when a first time slice is before a second time slice on a time axis, the target time period is the last two time windows of the first time slice; the target time period is the first two time windows of the first time slice when the first time slice is located after the second time slice on the time axis.

In an example, the time splicing module 73 is further configured to, before splicing the target time period of the first time slice with the second time slice, subtract the minimum timestamp of the timestamp interval corresponding to the target time period from the timestamp of each single event in the target time period, and add a timestamp interval difference to the timestamp of each single event in the second time slice, where the timestamp interval difference is a maximum timestamp minus a minimum timestamp in the timestamp interval.

In one example, the event filtering module 74, when configured to remove the target single event in the first time slice, includes: and if the time stamp of at least one single event exists in the double coincidence or the triple coincidence obtained after the time sequencing of the first time slice, the at least one single event is removed.

In an example, the time splicing module 73 is specifically configured to perform control through a first state machine and a second state machine; the first state machine is used for respectively writing the time stamp of each single event in the target time period of the first time slice and the time stamp of each single event in the second time slice into a preset memory by controlling jumping among a plurality of states so as to splice the time stamp in the target time period and the time stamp of the second time slice in the memory; and the second state machine is used for sending the time stamp in the memory to a coincidence judgment module for coincidence judgment when the effective time stamp exists in the target time slice of the first time slice or the second time slice by controlling the jumping among a plurality of states.

The functions of the event matching determination method according to the present disclosure may be stored in a computer-readable storage medium if they are implemented in the form of software functional units and sold or used as independent products. Based on such understanding, the technical solution of the present disclosure may be embodied in the form of a software product, which is stored in a storage medium and includes instructions for causing a control and processing device to execute all or part of the steps of the method according to the embodiments of the present disclosure. And the aforementioned storage medium includes: a U-disk, a removable hard disk, a Read-Only Memory (ROM), a Random Access Memory (RAM), a magnetic disk or an optical disk, and other various media capable of storing program codes.

The above description is only exemplary of the present disclosure and should not be taken as limiting the disclosure, as any modification, equivalent replacement, or improvement made within the spirit and principle of the present disclosure should be included in the scope of the present disclosure.

Claims

1. A method of image reconstruction, the method comprising:

acquiring single events of a first time slice and a second time slice;

and reconstructing an image according to the coincidence event.

2. The method of claim 1,

when the first time slice is before a second time slice on a time axis, the target time period is the last two time windows of the first time slice;

the target time period is the first two time windows of the first time slice when the first time slice is located after the second time slice on the time axis.

3. The method of claim 1, wherein after the time ordering the single events collected within the first time slice and the second time slice, respectively, and before the splicing the target time period of the first time slice with the second time slice, the method further comprises:

subtracting the minimum time stamp of the time stamp interval corresponding to the target time period from the time stamp of each single event in the target time period;

and adding a timestamp interval difference value to the timestamp of each single event in the second time slice, wherein the timestamp interval difference value is the maximum timestamp minus the minimum timestamp in the timestamp interval.

4. The method of claim 1, wherein removing the target single event in the first time slice, the target single event being a single event within a second time window of the time-ordered coincident events, comprises:

and if the time stamp of at least one single event exists in the double coincidence or the triple coincidence obtained by the first time slice after the time sequencing is positioned in the second time window, removing the at least one single event.

5. The method of claim 1, wherein the splicing the target time period of the first time slice with the second time slice to obtain a new time slice comprises:

controlling through a first state machine and a second state machine;

the first state machine is used for respectively writing the time stamp of each single event in the target time period of the first time slice and the time stamp of each single event in the second time slice into a preset memory by controlling jumping among a plurality of states so as to splice the time stamp in the target time period and the time stamp of the second time slice in the memory;

and the second state machine is used for sending the time stamp in the memory to a coincidence judgment module for coincidence judgment when the effective time stamp exists in the target time slice of the first time slice or the second time slice by controlling the jumping among a plurality of states.

6. An image reconstruction apparatus, characterized in that the apparatus comprises:

7. The apparatus of claim 6,

8. The apparatus of claim 6,

the time splicing module is further configured to, before splicing the target time period of the first time slice with the second time slice, subtract the minimum timestamp of the timestamp interval corresponding to the target time period from the timestamp of each single event in the target time period, and add a timestamp interval difference to the timestamp of each single event in the second time slice, where the timestamp interval difference is obtained by subtracting the minimum timestamp from the maximum timestamp in the timestamp interval.

9. The apparatus of claim 6,

the event filtering module, when configured to remove a target single event in a first time slice, includes: and if the time stamp of at least one single event exists in the double coincidence or the triple coincidence obtained by the first time slice after the time sequencing is positioned in the second time window, removing the at least one single event.

10. The apparatus of claim 6,

the time splicing module is specifically used for controlling through a first state machine and a second state machine; the first state machine is used for respectively writing the time stamp of each single event in the target time period of the first time slice and the time stamp of each single event in the second time slice into a preset memory by controlling jumping among a plurality of states so as to splice the time stamp in the target time period and the time stamp of the second time slice in the memory; and the second state machine is used for sending the time stamp in the memory to a coincidence judgment module for coincidence judgment when the effective time stamp exists in the target time slice of the first time slice or the second time slice by controlling the jumping among a plurality of states.